This disclosure relates to the field of apparatus, systems, compositions, and methods for analysis of particles, including imaging of particles in fluid samples, using wholly or partly automated devices to discriminate and quantify particles such as blood cells in the sample. The present disclosure also relates to a particle and/or intracellular organelle alignment liquid (PIOAL) useful for analyzing particles in a sample from a subject, methods for producing the liquid, and methods for using the liquid to detect and analyze particles. Compositions, systems, devices and methods useful for conducting image-based biological fluid sample analysis are also disclosed. The compositions, systems, devices, and methods of the present disclosure are also useful for detecting, counting and characterizing particles in biological fluids such as red blood cells, reticulocytes, nucleated red blood cells, platelets, and for image and morphologically-based white blood cell differential counting, categorization, subcategorization, characterization and/or analysis.
Blood cell analysis is one of the most commonly performed medical tests for providing an overview of a patient's health status. A blood sample can be drawn from a patient's body and stored in a test tube containing an anticoagulant to prevent clotting. A whole blood sample normally comprises three major classes of blood cells including red blood cells (erythrocytes), white blood cells (leukocytes) and platelets (thrombocytes). Each class can be further divided into subclasses of members. For example, five major types or subclasses of white blood cells (WBCs) have different shapes and functions. White blood cells may include neutrophils, lymphocytes, monocytes, eosinophils, and basophils. There are also subclasses of the red blood cell types. The appearances of particles in a sample may differ according to pathological conditions, cell maturity and other causes. Red blood cell subclasses may include reticulocytes and nucleated red blood cells.
A blood cell count estimating the concentration of RBCs, WBCs or platelets can be done manually or using an automatic analyzer. When blood cell counts are done manually, a drop of blood is applied to a microscope slide as a thin smear. Traditionally, manual examination of a dried, stained smear of blood on a microscope slide has been used to determine the number or relative amounts of the five types of white blood cells. Histological dyes and stains have been used to stain cells or cellular structures. For example, Wright's stain is a histologic stain that has been used to stain blood smears for examination under a light microscope. A Complete Blood Count (CBC) can be obtained using an automated analyzer, one type of which counts the number of different particles or cells in a blood sample based on impedance or dynamic light scattering as the particles or cells pass through a sensing area along a small tube. The automated CBC can employ instruments or methods to differentiate between different types of cells that include RBCs, WBCs and platelets (PLTs), which can be counted separately. For example, a counting technique requiring a minimum particle size or volume might be used to count only large cells. Certain cells such as abnormal cells in the blood may not be counted or identified correctly. Small cells that adhere to one another may be erroneously counted as a large cell. When erroneous counts are suspected, manual review of the instrument's results may be required to verify and identify cells.
Automated blood cell counting techniques can involve flow cytometry. Flow cytometry involves providing a narrow flow path, and sensing and counting the passage of individual blood cells. Flow cytometry methods have been used to detect particles suspended in a fluid, such as cells in a blood sample, and to analyze the particles as to particle type, dimension, and volume distribution so as to infer the concentration of the respective particle type or particle volume in the blood sample. Examples of suitable methods for analyzing particles suspended in a fluid include sedimentation, microscopic characterization, counting based on impedance, and dynamic light scattering. These tools are subject to testing errors. On the other hand, accurate characterization of types and concentration of particles may be critical in applications such as medical diagnosis.
In counting techniques based on imaging, pixel data images of a prepared sample that may be passing through a viewing area are captured using a microscopy objective lens coupled to a digital camera. The pixel image data can be analyzed using data processing techniques, and also displayed on a monitor.
Aspects of automated diagnosis systems with flowcells are disclosed in U.S. Pat. No. 6,825,926 to Turner et al. and in U.S. Pat. Nos. 6,184,978; 6,424,415; and 6,590,646, all to Kasdan et al., which are hereby incorporated by reference as if set forth fully herein.
Automated systems using dynamic light scattering or impedance have been used to obtain a complete blood count (CBC): total white blood cell count (WBC), total cellular volume of red blood cells (RBC distribution), hemoglobin HGB (the amount of hemoglobin in the blood); mean cell volume (MCV) (mean volume of the red cells); MPV (mean PLT volume); hematocrit (HCT); MCH (HGB/RBC) (the average amount of hemoglobin per red blood cell); and MCHC (HGB/HCT) (the average concentration of hemoglobin in the cells). Automated or partially automated processes have been used to facilitate white blood cell five part differential counting and blood sample analyses.
Although such currently known particle analysis systems and methods, along with related medical diagnostic techniques, can provide real benefits to doctors, clinicians, and patients, still further improvements are desirable. For example, there is a continuing need for improved methods and compositions useful for particle and/or intracellular organelle alignment when performing image-based sample analysis using automated systems. Embodiments of the present invention provide solutions for at least some of these outstanding needs.